Alkali-soluble resins (ASRs) were prepared by (i) solution and (ii) emulsion polymerization. All ASRs were synthesized with number-average molar masses < 20,000 g mol-1 and all had 15 wt% methacrylic acid 5 wt% styrene, the remaining 80 wt% was composed of either methyl methacrylate or a combination of methyl methacrylate and ethyl acrylate. All emulsion ASRs were made to 20% solids, with volume-average particle diameters (dv) in the region 30 – 50 nm, with a glass transition temperature of 80 – 120 °C. Emulsion polymerization was the preferred route for ASR synthesis, to allow further studies on their dissolution behaviour. Before their use as colloidal stabilizers, the dissolution behaviour of the ASRs needed to beinvestigated e.g. effect of temperature, molar mass, and composition. Particle size and absorbance measurements were taken during dissolution of ASRs to achieve 100%neutralization and these were shown to have two stages, an apparent particle swelling (whichwas rapid), and a slower, decrease in particle size as water-soluble polymeric material wasdiffusing out of the ASR particles. From this, further interpretation allowed for calculating the diffusion coefficient of the ASR polymer using the Stokes-Einstein equation. Time-domain nuclear magnetic resonance (TD-NMR) was employed to enhance understanding of what is occurring in the ASR particles, and in the aqueous, continuous phase. The final aspect of this project was to use the ASRs prepared as colloidal stabilizers in emulsion polymerizations of butyl acrylate (BA) and butyl methacrylate (BMA) using varying levels and also the effect of adding additional surfactant. The results show that the effect of ASR molar mass, the concentration of stabilizer, and also the impact of the EA-containing ASR greatly influence stability, whereby lower ASR molar mass, higher levels of stabilizer and including EA greatly benefit colloidal stability in PBA latexes. In PBMA latexes, a similar trend was also observed, but, the presence of ethyl acrylate (EA) in the ASR backbone has a detrimental effect on the colloidal stability, caused by the inability of grafting to occur between the ASR and PBMA.

Polymer chain microstructure, including characteristics such as molecular weight and branch length, can impact the end-use properties of the polymer. The assumptions contained in deterministic models prevent examination of the structure of individual polymer chains, so removal of these assumptions is necessary to gain insight into molecular-level mechanisms that determine chain microstructure. The work presented here uses a combination of stochastic and deterministic models to examine two significant mechanistic issues in free radical polymerization. The zero-one assumption concerning the number of radicals is often made for miniemulsion polymerization using oil-soluble initiators because of accelerated termination due to radical confinement. Although most of the initiator is present inside the particles, opposing viewpoints exist as to whether the locus of radical generation is the particle phase or the aqueous phase. A well-mixed kinetic Monte Carlo (KMC) model is used to simulate the molecular weight distribution and the results are compared to estimated molecular weights for several chain-stopping events, with the finding that the dominant nucleation mechanism varies with reaction temperature and particle size. Intramolecular chain transfer to polymer, or backbiting, is often assumed to produce only short-chain branches. Using a lattice KMC model, a cumulative distribution function (CDF) is obtained for branch lengths produced by backbiting. Implementation of the CDF in both a rate-equation model and the well-mixed KMC model shows that, for the butyl acrylate solution polymerization system used for comparison, backbiting is responsible for most of the branches, including long-chain branches, even though overlap of the polymer coils in the solution is predicted, a condition which would normally be expected to lead to significant intermolecular chain transfer to polymer. The well-mixed KMC model provides a more thorough analysis of chain microstructure while the rate-equation model is more computationally efficient.